Technologies that would enable the generation of soluble proteins for use as reagents in drug discovery efforts and as therapeutic entities represent a significant unmet need in drug discovery. One method for increasing solubility is the introduction of appropriate mutations. A general, robust, and efficient method for identifying mutations that will confer solubility to a protein of interest would have tremendous commercial value. This proposal seeks to employ an innovative technology, Protein Design Automation(r) (PDATM), to improve the solubility of an important protein therapeutic, interferon beta. Currently, interferon beta is the primary treatment for multiple sclerosis. However, interferon beta forms aggregates because of poor solubility, resulting in decreased efficacy and increased immunogenicity of this therapeutic. Furthermore, interferon beta forms inclusion bodies during expression in E. coli. The resulting high production costs thus hinder further development of improved variants. Interferon beta variants with improved solubility would have significant commercial potential and benefit patients through increased efficacy and decreased side effects. The research design strategy to achieve a soluble interferon beta variant includes performing rational protein design calculations, constructing a library of improved variants that are predicted to have improved solubility, identifying soluble variants with high throughput screening methods, and testing these improved variants for solubility and activity. After validation of this computational and experimental design strategy, long term aims of this proposal are to improve the solubility of additional protein therapeutics and to provide the service of solubility optimization to facilitate external drug discovery efforts.